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Zeitschriftenartikel:

W. Rohringer, R. Bücker, S. Manz, Th. Betz, C. Koller, M. Göbel, A. Perrin, H.-J. Schmiedmayer, Thorsten Schumm:
"Stochastic optimization of a cold atom experiment using a genetic algorithm";
Applied Physics Letters, 93 (2008), 264101; S. 264101-1 - 264101-3.



Kurzfassung englisch:
We employ an evolutionary algorithm to automatically optimize different stages of a cold atom experiment without human intervention. This approach closes the loop between computer based experimental control systems and automatic real time analysis and can be applied to a wide range of experimental situations. The genetic algorithm quickly and reliably converges to the most performing parameter set independent of the starting population. Especially in many-dimensional or connected parameter spaces, the automatic optimization outperforms a manual search.


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1063/1.3058756

Elektronische Version der Publikation:
http://publik.tuwien.ac.at/files/PubDat_172008.pdf


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.